Groundwater recharge

Satellite(s) e.g., MODIS, Sentinel-2.	Monitoring element Land spectral reflectance.

Satellite(s)

e.g., MODIS, Sentinel-2.

Monitoring element

Land spectral reflectance.

Description technique

Westerhoff et al. (2018) used a nationwide model of groundwater recharge for New Zealand (NGRM; 1km x 1km model grid; Westerhoff et al. 2016) that combines large scale satellite data and local datasets to assess groundwater recharge and its uncertainty. This approach also compared groundwater recharge model results to actual measurements.

Accuracy / Resolution

NGRM uncertainty of 17%.

Case study

New Zealand (Canterbury Plains and Mid-Mataura Catchment in Southland).

Also fits domain

Land.

Benefits

Satellite data of evapotranspiration and vegetation improve the spatial characteristics of the recharge model.
Case study comparisons indicated that the nationwide rainfall recharge model gives a valuable initial estimate when applied at the local or regional scale, and can thus also be used in areas as a valuable initial estimate in data-sparse areas.

Limitations

This approach as such, presents some limitations for local application: the resolution of MODIS-derived parameters is limited and model calibration might be required.
It is recommended to carefully consider the NGRM model limitations for local application.

Applicability for Northland

Yes. Depending on the scale, model calibration and utilisation of finer resolution imagery might be required.

Techniques applying optical data will be limited in coverage and temporal granularity by the persistent cloud cover in the region, particularly during the winter months. Mature cloud-masking techniques are directly available for open access multispectral data (e.g. Landsat and Sentinel-2). When using commercial data, care must be taken to ensure that there is sufficiently cloud free imagery available, as cloud masking is not as mature, and ordering a large volume of imagery to ensure complete cloud free coverage between multiple observations can become cost prohibitive.

Publication references

Westerhoff R, White P, Rawlinson Z. 2018. Incorporation of Satellite Data and Uncertainty in a Nationwide Groundwater Recharge Model in New Zealand. Remote Sensing. 10(1):58.

https://www.mdpi.com/2072-4292/10/1/58

Other comments or information

Other references

Westerhoff R, White P, Rawlinson Z. 2016. Application of global models and satellite data for smaller-scale groundwater recharge studies. Hydrol Earth Syst Sci Discuss. 2016:1-36. doi:10.5194/hess-2016-410.

https://www.hydrol-earth-syst-sci-discuss.net/hess-2016-410/

Mourot F, Westerhoff R, Macdonald N, Cameron S. 2019. Better spatial characterisation of evapotranspiration and rainfall recharge estimates to groundwater using remote sensing multispectral techniques at lysimeter sites. Lower Hutt (NZ). 82 p.

https://www.envirolink.govt.nz/assets/1951-HBRC245-Better-spatial-characterisation-of-evapotranspiration-and-rainfall-recharge-estimates-to-groundwater-using-remote-sensing-multispectral-techniques-at-lysimeter-sites.pdf-.pdf

Swaffer BA, Habner NL, Holland KL, Crosbie RS. 2020. Applying satellite-derived evapotranspiration rates to estimate the impact of vegetation on regional groundwater flux. Ecohydrology. 13(1):e2172. doi:10.1002/eco.2172.
https://onlinelibrary.wiley.com/doi/abs/10.1002/eco.2172

Ruggieri G, Allocca V, Borfecchia F, Cusano D, Marsiglia P, De Vita P. 2021. Testing Evapotranspiration Estimates Based on MODIS Satellite Data in the Assessment of the Groundwater Recharge of Karst Aquifers in Southern Italy. Water. 13(2):118.

https://www.mdpi.com/2073-4441/13/2/118